Adaptive Event Triggered Optimal Control for Constrained Continuous-time Nonlinear Systems

被引：0
作者：
Ping Wang
Zhen Wang
Qian Ma
机构：
[1] Shandong University of Science and Technology,College of Mathematics and Systems Science
[2] Qingdao Agricultural University,College of Science and Information
[3] Nanjing University of Science and Technology,School of Automation
来源：
International Journal of Control, Automation and Systems | 2022年 / 20卷
关键词：
ADP; constrained input; event-triggered; neural networks; optimal control;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper considers the event-triggered optimal control (ETOC) strategy for constrained continuous-time nonlinear systems via adaptive dynamic programming (ADP). First, a novel event-triggering condition is proposed, which can guarantee the stability of the closed-loop system. Meanwhile, the existence of a lower bound for the execution time is proved, which can guarantee that the designed event-trigger scheme avoids Zeno behavior. Then, to solve the partial differential Hamilton-Jacobi-Bellman (HJB) equation, the critic Neural Network (NN) is designed to approximate the cost function. So that the ADP-based ETOC scheme is designed. Moreover, through Lyapunov stability analysis, the stability of the closed-loop system can be ensured. Also, the uniform ultimate boundedness of the states and the weight estimation error can also be guaranteed. Last, a numerical example is given to illustrate the effectiveness and advantages of the proposed control scheme.
引用
收藏
页码：857 / 868
页数：11
相关论文
共 67 条
[1]  
Zhu Y Z(2020)Quasi-synchronization of discrete-time Lur’e-type switched systems with parameter mismatches and relaxed PDT constraints IEEE Transactions on Cybernetics 50 2026-2036
[2]  
Zheng W X(2020)Observer-based control for cyber-physical systems with periodic DoS attacks via a cyclic switching strategy IEEE Transactions on Automatic Control 65 3714-3721
[3]  
Zhou D H(2020)Multiple Lyapunov functions analysis approach for discrete-time-switched piecewise-affine systems under dwell-time constraints IEEE Transactions on Automatic Control 65 2177-2184
[4]  
Zhu Y Z(2011)On event design in event-triggered feedback systems Automatica 47 2319-2322
[5]  
Zheng W X(2017)Approximate optimal control of affine nonlinear continuous-time systems using event-sampled neurodynamic programming IEEE Transactions on Neural Networks and Learning Systems 28 639-652
[6]  
Zhu Y Z(2020)Event-triggered optimal control with performance guarantees using adaptive dynamic programming IEEE Transactions on Neural Networks and Learning Systems 31 76-88
[7]  
Zheng W X(2005)Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach Automatica 41 779-791
[8]  
Wang X F(2017)An iterative relaxation approach to the solution of the Hamilton-Jacobi-Bellman-Isaacs equation in nonlinear optimal control IEEE/CAA Journal of Automatica Sinica 5 360-366
[9]  
Lemmon M(2020)Distributed control of nonlinear multiagent systems with unknown and nonidentical control directions via event-triggered communication IEEE Transactions on Cybernetics 50 1820-1832
[10]  
Sahoo A(2009)Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints IEEE Transactions on Neural Networks 20 1490-1503
1234567